VP Enterprise Data Platform

Surescripts serves the nation through simpler, trusted health intelligence sharing, in order to increase patient safety, lower costs and ensure quality care. We deliver insights at critical points of care for better decisions - from streamlining prior authorizations to delivering comprehensive medication histories to facilitating messages between providers.

The VP Enterprise Data Platform leads the core technical foundation of our enterprise data ecosystem. This role reports to the Chief Data and Analytics Officer and is accountable for building, operating, and evolving the data engineering capabilities that ensure our data is trusted, observable, scalable, and ready for advanced analytics, product innovation, and AI-enabled solutions.

The VP Enterprise Data Platform leads teams responsible for data quality, data observability, data engineering, data governance, and database management, and will play a critical leadership role in Surescripts' enterprise transition to a modern medallion data architecture on Google Cloud Platform.

This role partners closely with Enterprise Analytics, Data Solutions, Product Innovation, and Network Technology and Operations (NT&O) teams to ensure seamless handoff of production-ready, analytics-optimized data assets.

• Oversee the design, implementation, and adoption of a modern medallion data architecture (Bronze, Silver, Gold) on Google Cloud Platform
• Own the enterprise common data model, ensuring consistency, scalability, and extensibility across domains and use cases
• Oversee the design and maintenance of a robust semantic layer that supports governed, self-service analytics across the Surescripts analytics platform which includes Tableau and Looker
• Establish architectural standards and best practices for data ingestion, transformation, storage, and access

• Build, mentor, and retain high-performing data engineering and analytics engineering teams
• Establish modern engineering standards (cloud-native, meta-data-driven, AI-enabled, automated, resilient) to drive continuous improvements in cost-efficiency, velocity, and platform performance
• Ensure high performance, reliability, and scalability of enterprise data platforms supporting mission-critical healthcare workflows
• Partner with technology infrastructure and security teams to ensure data platforms meet availability, security, and compliance requirements

• Lead development and management of enterprise-wide data quality standards, monitoring, and remediation processes
• Implement data observability capabilities to proactively detect, diagnose, and resolve data issues across pipelines and platforms
• Ensure consumers of data can trust the accuracy, completeness, and timeliness of enterprise data assets
• Establish and operate data quality and certification frameworks, ensuring analytic and customer-facing data assets meet defined trust and readiness thresholds

• Own and lead the enterprise data governance function, establishing standards, policies, and controls that ensure data is trusted, consistent, secure, and audit-ready across the organization.
• Define and enforce enterprise data standards, including naming conventions, data definitions, metadata, lineage, and lifecycle management across the medallion architecture.
• Embed data governance into engineering workflows, including pipeline design, data quality rules, observability, access controls, and semantic modeling.
• Partner with the Enterprise Analytics and domain leaders to enable federated data stewardship, aligning technical governance with business meaning and metric definitions

• Own the technical implementation and administration of Looker, including LookML development, modeling standards, and performance optimization
• Ensure data models and semantic layers are designed to support both internal decision-making, new data product development, and external customer-facing analytics and reporting
• Collaborate with the VP of Enterprise Analytics and Data Solutions to align technical data assets with analytics, reporting, insight, and product needs

• Bachelor's degree in a related field such as computer science, data science, statistics, business administration, or a related discipline.
• 12+ years of progressive experience in data engineering, data platform, or data architecture roles, with at least 5 years in a leadership role.
• Proven experience designing and operating large-scale, cloud-based data platforms, preferably on Google Cloud Platform
• Deep expertise in modern data architectures, including medallion/Lakehouse patterns, dimensional modeling, and semantic layers
• Strong experience with data quality, data observability, and production data operations
• Hands-on experience implementing and managing Looker, including LookML and governed analytics models
• Demonstrated ability to lead teams through complex…